Probabilistic Methods for Increased Robustness in Machine Learning
Explore probabilistic methods to enhance machine learning robustness, focusing on latent variables, molecular design, and optimization techniques for improved AI performance and reliability.
Anomaly Detection in Hyperspectral Imaging - Neal Gallagher
Explore advanced anomaly detection techniques in hyperspectral imaging, focusing on GLS, ELS, and WPCA methods for improved sensitivity and selectivity in detecting minor signals within complex mixtures.
Preprocessing Revisited
Explore new developments in chemometric preprocessing, including multi-block strategies and Variable Sorting for Normalization, to reduce unwanted variability in experimental data.
Effective Data Visualisation - With Valentina D'Efilippo
Explore innovative data visualization techniques beyond standard charts with designer Valentina D'Efilippo. Learn to create impactful visual stories through creative approaches, empathy, and unique perspectives on data representation.
The 10 Equations That Rule the World - With David Sumpter
Explore 10 key mathematical equations and their real-world applications in finance, relationships, social media, and personal development with Professor David Sumpter.
Big Data - They Know Everything About You
Explore the clash between privacy and security in the era of big data, examining its impact on personal information, technological advancements, and potential for preventing terrorism.
Machine Learning and Data Science for Medicine - A Vision, Some Progress and Opportunities
Explore machine learning and data science applications in medicine, focusing on AutoPrognosis - an automated system for creating tailored, interpretable, and accurate prognostic models for various diseases.
Does Campaigning on Social Media Make a Difference? Evidence from Candidate Use of Twitter
Explore the impact of social media campaigning on elections using data science. Analyze Twitter usage by candidates, voter engagement, and campaign strategies to understand modern political landscapes.
Digital Data Products and Changing Conversations - Dr Ryan Dunn, Department for Work and Pensions
Exploring data science's role in public discourse, this talk addresses challenges in using data for decision-making and fostering trust in statistics, emphasizing accessibility and transparency.
How Digital Data Collection Methods Impact Scientific Inference - Dr. Rebekah Tromble
Explore how digital data collection methods impact scientific inference, focusing on Twitter data analysis, APIs, and logit regression. Learn to navigate challenges in social and cultural research.
Simulation - The Challenge for Data Science
Exploring the fusion of simulation models and machine learning for policy analysis, addressing challenges in parameter estimation and initialization for complex systems forecasting.
Introduction to Data Ethics - Brent Mittelstadt
Explore data ethics with Dr. Mittelstadt, covering algorithmic fairness, accountability, transparency, and privacy. Learn about ethical challenges in AI and data analytics, with real-world examples and regulatory insights.
Data Science Applications - Environment/Ecology
Explore statistical modeling techniques for ecological data, focusing on hidden Markov models, Bayesian inference, and capture-recapture methods. Learn to analyze and interpret complex environmental datasets.
Inference with Neural Nets
Explore neural network inference, covering mathematical foundations, data science concepts, and practical tools like PyTorch. Gain insights into advanced topics and real-world applications.
Graph Convolutional Networks - GCNs
Explore Graph Convolutional Networks: from traditional ConvNets to spectral and spatial approaches. Learn architectures, implementations, and applications of GCNs in this comprehensive lecture.
Can Data Make a Medicine? - With Patrick Vallance
Explore how real-time data and open-source information revolutionize medicine development, from identifying molecules to conducting clinical trials and improving patient care.
The ABC of Smart Machines - With Danielle George
Explore radio astronomy, cutting-edge telescopes, and data-driven cosmic discoveries with Professor Danielle George. Learn about engineering challenges and innovative technologies shaping our understanding of the universe.
Affine Spline Insights into Deep Learning - Richard Baraniuk, Rice University
Explore deep learning through affine splines, understanding neural networks as matched filterbanks and partition-based signal distances. Gain insights into data augmentation and future research directions.
Insights from Predictive Policing - Tobias Brandt, Rotterdam School of Management
Explore data-driven decision-support in policing, examining the complex relationship between prediction quality and decision outcomes. Learn about end-to-end frameworks for model selection in smart city operations.
Geospatial Standards for Data Science - Dr. Gobe Hobona, OGC
Explore geospatial data standards for efficient sharing across sectors. Learn about OGC's role in developing interface standards and their impact on data science and defense applications.
The Defence Context - Geospatial Standards for Data Science
Explore geospatial standards in data science for defense, covering interoperability, machine learning, and emerging technologies to enhance information sharing and decision-making.